Just integrated the Wordtune API to clean up a batch of customer feedback exports. Needed to standardize phrasing for our analytics pipeline. The official tools didn't fit our simple, repetitive workflow.
The script loops through .txt files in a folder, sends the text to the API for rewriting (using the 'formal' tone), and saves the output. Uses a simple config file for the API key. Anyone else doing this? Main hurdle was rate limiting—had to build in a delay. Looking for a more robust error handling approach.
Putting an API key in a plain config file for a batch process is a bad habit. Use your platform's secret manager (Secrets Manager, Vault, even environment variables loaded at runtime). That script is one permission mistake away from leaking it.
For rate limiting, consider an exponential backoff with jitter instead of a fixed delay. Basic error handling should catch HTTP 429/503 and retry, log the specific file that failed, and move on. Don't let one failure stop the whole batch.
What are you doing with the processed data? If it's customer feedback, check your terms of service on sending that externally. Might be a compliance red flag.
SecDevOps
Nice! I've done something similar, but for standardizing support ticket summaries. That fixed delay for rate limiting will bite you once the batch grows. I ended up using a simple retry decorator with a random wait - it's a few extra lines but saves the job dying halfway.
Also, watch out for the formal tone on some types of feedback. It can sometimes strip out the emotional nuance that's actually valuable in the analytics. I now run a small sample first to check the output isn't getting too sterilized. What's your final step after the rewrite - pushing it into a BI tool?
Good point on the secret manager. For our small team, even a .env file loaded at runtime is a step up from plain config, and it's what we can manage right now.
The compliance angle is huge, I hadn't thought about that. We're just aggregating anonymized snippets for internal sentiment tracking, but you're right, I need to double-check our data agreement.
Do you have a go-to pattern for that error handling? Something simple that doesn't need a full library?
StartupSeeker
The fixed delay approach for rate limiting is a start, but it's inefficient and brittle as your dataset scales. You'll end up paying for idle time. A better pattern is a simple retry loop with incremental backoff. It saves money on compute runtime in the long term.
For error handling, you don't need a library. Wrap your API call in a try block, catch specific HTTP status codes, and implement a retry counter. Log the failing filename and the error, then continue. This prevents a single failure from halting the entire batch, which is crucial for cost-effective batch operations.
What's the average runtime of your script per batch, and where is it hosted? Even a small, consistently running EC2 instance or Lambda function for this could have its costs trimmed.
Less spend, more headroom.